Role of BRC in arid rock weathering

Plot all alpha diversity metrics together

Richness_Diversity_long[Richness_Diversity_long$Metric != "Chao1" &
                          Richness_Diversity_long$Metric != "Inv. Simpson" &
                          Richness_Diversity_long$Metric != "Berger Parker", ] %>% 
  droplevels() ->
  Richness_Diversity_long2plot

p_alpha <- ggplot(Richness_Diversity_long2plot, aes(
  x = Source,
  y = Estimate
)) +
  geom_violin(aes(colour = Climate, fill = Climate), alpha = 1/3) +
  geom_jitter(aes(colour = Climate, fill = Climate), shape = 16, size = 2, width = 0.2, alpha = 2/3) +
  scale_colour_manual(values = pom4, name = "") +
  scale_fill_manual(values = pom4, name = "") +
  theme_cowplot(font_size = 11, font_family = f_name) +
  # geom_errorbar(alpha = 1 / 2, width = 0.3) +
  xlab("") +
  ylab("") +
  theme(axis.text.x = element_text(
    angle = 45,
    vjust = 0.9,
    hjust = 0.9
  )) +
  facet_grid(Metric ~ Climate, shrink = FALSE, scale = "free") +
  background_grid(major = "y",
                  minor = "none") +
  theme(panel.spacing = unit(2, "lines"))

dat_text <- data.frame(
  label = as.character(fct_c(ph_Sobs$groups$groups, ph_ACE$groups$groups, ph_Shannon$groups$groups)),
  Metric   = rep(levels(Richness_Diversity_long2plot$Metric), each = 6),
  Climate = str_split(rownames(ph_Sobs$groups), ":", simplify = TRUE)[, 1], 
  x = c("Loess soil", "Loess soil", "Limestone", "Dust", "Dolomite", "Dust"),
  # x     = as.factor(levels(Richness_Diversity_long2plot$Climate.Source)),
  y = rep(c(460, 850, 6.5), each = 6)
  # y = rep(c(40, 140, 0.5), each = 6)
)


p_alpha <- p_alpha + geom_text(
  data    = dat_text,
  mapping = aes(x = x, y = y, label = label),
  nudge_x = -0.2,
  nudge_y = -0.1
)

print(p_alpha)

Richness_Diversity_long2plot %>%
  group_by(Metric, Climate.Source) %>%   # the grouping variable
  summarise(mean_PL = mean(Estimate),  # calculates the mean of each group
            sd_PL = sd(Estimate), # calculates the standard deviation of each group
            n_PL = n(),  # calculates the sample size per group
            SE_PL = sd(Estimate)/sqrt(n())) %>% # calculates the standard error of each group
  kable(.) %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = F)

1. Possible changes in biofilm arid vs hyper arid

Is there a difference between the two sites. However, since we know that that samples are of different nature we’ll have to control for rock type, source and location:

(mod1 <-  adonis(
  otu_table(Rock_weathering_filt3_GMPR) ~ Climate * Source * Location,
  data = as(sample_data(Rock_weathering_filt3_GMPR), "data.frame"),
  method = "horn",
  permutations = 9999
))

## 
## Call:
## adonis(formula = otu_table(Rock_weathering_filt3_GMPR) ~ Climate *      Source * Location, data = as(sample_data(Rock_weathering_filt3_GMPR),      "data.frame"), permutations = 9999, method = "horn") 
## 
## Permutation: free
## Number of permutations: 9999
## 
## Terms added sequentially (first to last)
## 
##                  Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
## Climate           1      2.53   2.530   21.38 0.216 0.0001 ***
## Source            3      4.71   1.569   13.26 0.402 0.0001 ***
## Location          1      0.49   0.487    4.12 0.042 0.0042 ** 
## Climate:Source    1      0.44   0.440    3.72 0.038 0.0039 ** 
## Climate:Location  1      0.46   0.461    3.89 0.039 0.0042 ** 
## Source:Location   1      0.11   0.114    0.97 0.010 0.4907    
## Residuals        25      2.96   0.118         0.253           
## Total            33     11.70                 1.000           
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Rock_weathering_filt3_GMPR_Arid <- subset_samples(Rock_weathering_filt3_GMPR, Climate == "Arid")
Rock_weathering_filt3_GMPR_Arid <- filter_taxa(Rock_weathering_filt3_GMPR_Arid, function(x) sum(x) > 0, TRUE)
(mod2 <-  adonis(
  otu_table(Rock_weathering_filt3_GMPR_Arid) ~ Source * Location,
  data = as(sample_data(Rock_weathering_filt3_GMPR_Arid), "data.frame"),
  method = "horn",
  permutations = 9999
))

## 
## Call:
## adonis(formula = otu_table(Rock_weathering_filt3_GMPR_Arid) ~      Source * Location, data = as(sample_data(Rock_weathering_filt3_GMPR_Arid),      "data.frame"), permutations = 9999, method = "horn") 
## 
## Permutation: free
## Number of permutations: 9999
## 
## Terms added sequentially (first to last)
## 
##           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
## Source     2      2.31   1.153    7.34 0.479 0.0001 ***
## Location   1      0.47   0.469    2.99 0.097 0.0143 *  
## Residuals 13      2.04   0.157         0.424           
## Total     16      4.82                 1.000           
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Rock_weathering_filt3_GMPR_Hyperarid <- subset_samples(Rock_weathering_filt3_GMPR, Climate == "Hyperarid")
Rock_weathering_filt3_GMPR_Hyperarid <- filter_taxa(Rock_weathering_filt3_GMPR_Hyperarid, function(x) sum(x) > 0, TRUE)
(mod3 <-  adonis(
  otu_table(Rock_weathering_filt3_GMPR_Hyperarid) ~ Source * Location,
  data = as(sample_data(Rock_weathering_filt3_GMPR_Hyperarid), "data.frame"),
  method = "horn",
  permutations = 9999
))

## 
## Call:
## adonis(formula = otu_table(Rock_weathering_filt3_GMPR_Hyperarid) ~      Source * Location, data = as(sample_data(Rock_weathering_filt3_GMPR_Hyperarid),      "data.frame"), permutations = 9999, method = "horn") 
## 
## Permutation: free
## Number of permutations: 9999
## 
## Terms added sequentially (first to last)
## 
##                 Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
## Source           2      2.85   1.423   18.62 0.654 0.0001 ***
## Location         1      0.47   0.473    6.19 0.109 0.0113 *  
## Source:Location  1      0.11   0.114    1.49 0.026 0.2420    
## Residuals       12      0.92   0.076         0.211           
## Total           16      4.35                 1.000           
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

#According to this model we see that indeed there’s an effect of site on the community (p = 0.001), and that effect accounts for about 17% of the variance. Also, considering that Location is only borderline significant and explains very little of the data, we could probably take it out of the model to make a minimal adequate model.

(mod4 <-  adonis(
  otu_table(Rock_weathering_filt3_GMPR) ~ Climate * Source,
  data = as(sample_data(Rock_weathering_filt3_GMPR), "data.frame"),
  method = "horn",
  permutations = 9999
))

## 
## Call:
## adonis(formula = otu_table(Rock_weathering_filt3_GMPR) ~ Climate *      Source, data = as(sample_data(Rock_weathering_filt3_GMPR),      "data.frame"), permutations = 9999, method = "horn") 
## 
## Permutation: free
## Number of permutations: 9999
## 
## Terms added sequentially (first to last)
## 
##                Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
## Climate         1      2.53   2.530   17.65 0.216 0.0001 ***
## Source          3      4.71   1.569   10.94 0.402 0.0001 ***
## Climate:Source  1      0.45   0.445    3.11 0.038 0.0086 ** 
## Residuals      28      4.01   0.143         0.343           
## Total          33     11.70                 1.000           
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(mod5 <-  adonis(
  otu_table(Rock_weathering_filt3_GMPR_Arid) ~ Source,
  data = as(sample_data(Rock_weathering_filt3_GMPR_Arid), "data.frame"),
  method = "horn",
  permutations = 9999
))

## 
## Call:
## adonis(formula = otu_table(Rock_weathering_filt3_GMPR_Arid) ~      Source, data = as(sample_data(Rock_weathering_filt3_GMPR_Arid),      "data.frame"), permutations = 9999, method = "horn") 
## 
## Permutation: free
## Number of permutations: 9999
## 
## Terms added sequentially (first to last)
## 
##           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
## Source     2      2.31   1.153    6.43 0.479  2e-04 ***
## Residuals 14      2.51   0.179         0.521           
## Total     16      4.82                 1.000           
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(mod6 <-  adonis(
  otu_table(Rock_weathering_filt3_GMPR_Hyperarid) ~ Source,
  data = as(sample_data(Rock_weathering_filt3_GMPR_Hyperarid), "data.frame"),
  method = "horn",
  permutations = 9999
))

## 
## Call:
## adonis(formula = otu_table(Rock_weathering_filt3_GMPR_Hyperarid) ~      Source, data = as(sample_data(Rock_weathering_filt3_GMPR_Hyperarid),      "data.frame"), permutations = 9999, method = "horn") 
## 
## Permutation: free
## Number of permutations: 9999
## 
## Terms added sequentially (first to last)
## 
##           Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
## Source     2      2.85   1.423    13.2 0.654  1e-04 ***
## Residuals 14      1.50   0.107         0.346           
## Total     16      4.35                 1.000           
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Final model

print(mod4)

## 
## Call:
## adonis(formula = otu_table(Rock_weathering_filt3_GMPR) ~ Climate *      Source, data = as(sample_data(Rock_weathering_filt3_GMPR),      "data.frame"), permutations = 9999, method = "horn") 
## 
## Permutation: free
## Number of permutations: 9999
## 
## Terms added sequentially (first to last)
## 
##                Df SumsOfSqs MeanSqs F.Model    R2 Pr(>F)    
## Climate         1      2.53   2.530   17.65 0.216 0.0001 ***
## Source          3      4.71   1.569   10.94 0.402 0.0001 ***
## Climate:Source  1      0.45   0.445    3.11 0.038 0.0086 ** 
## Residuals      28      4.01   0.143         0.343           
## Total          33     11.70                 1.000           
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

mod4_pairwise <- PairwiseAdonis(
  otu_table(Rock_weathering_filt3_GMPR),
  sample_data(Rock_weathering_filt3_GMPR)$Climate.Source,
  sim.function = "vegdist",
  sim.method = "horn",
  p.adjust.m = "BH"
)
print(mod4_pairwise)

##                                         pairs total.DF F.Model    R2 p.value p.adjusted
## 1           Arid dust vs Hyperarid loess soil        4    4.80 0.616  0.1000     0.1154
## 2                 Arid dust vs Hyperarid dust        3    2.99 0.599  0.3333     0.3333
## 3                 Arid dust vs Arid limestone       13    4.61 0.277  0.0094     0.0223
## 4             Arid dust vs Hyperarid dolomite       13    6.59 0.355  0.0119     0.0223
## 5                Arid dust vs Arid loess soil        4    5.36 0.641  0.1000     0.1154
## 6      Hyperarid loess soil vs Hyperarid dust        4   10.87 0.784  0.2000     0.2143
## 7      Hyperarid loess soil vs Arid limestone       14    5.59 0.301  0.0078     0.0223
## 8  Hyperarid loess soil vs Hyperarid dolomite       14   16.02 0.552  0.0028     0.0105
## 9     Hyperarid loess soil vs Arid loess soil        5   95.51 0.960  0.1000     0.1154
## 10           Hyperarid dust vs Arid limestone       13    5.34 0.308  0.0327     0.0545
## 11       Hyperarid dust vs Hyperarid dolomite       13   11.62 0.492  0.0118     0.0223
## 12          Hyperarid dust vs Arid loess soil        4  205.85 0.986  0.1000     0.1154
## 13       Arid limestone vs Hyperarid dolomite       23   21.90 0.499  0.0001     0.0015
## 14          Arid limestone vs Arid loess soil       14    9.11 0.412  0.0018     0.0090
## 15      Hyperarid dolomite vs Arid loess soil       14   16.84 0.564  0.0017     0.0090
##    sig
## 1     
## 2     
## 3    .
## 4    .
## 5     
## 6     
## 7    .
## 8    .
## 9     
## 10    
## 11   .
## 12    
## 13   *
## 14   *
## 15   *

sig_pairs <- as.character(mod4_pairwise$pairs[mod4_pairwise$p.adjusted < 0.05])
  
simper(otu_table(Rock_weathering_filt3_GMPR), sample_data(Rock_weathering_filt3_GMPR)$Climate.Source, parallel = 4)

## cumulative contributions of most influential species:
## 
## $`Arid dust_Hyperarid loess soil`
##    OTU6   OTU65  OTU838   OTU90  OTU596   OTU11  OTU187   OTU93  OTU746  OTU167  OTU711 
##   0.222   0.368   0.406   0.430   0.453   0.469   0.484   0.496   0.509   0.521   0.532 
##  OTU121  OTU144   OTU99  OTU194  OTU105  OTU356  OTU340  OTU115  OTU640   OTU55  OTU298 
##   0.543   0.553   0.562   0.571   0.579   0.586   0.593   0.599   0.606   0.612   0.619 
##  OTU715   OTU88  OTU197   OTU48  OTU221  OTU301 OTU1047  OTU322   OTU16  OTU586   OTU46 
##   0.625   0.631   0.638   0.643   0.649   0.654   0.659   0.665   0.669   0.674   0.678 
##  OTU172  OTU386   OTU67  OTU333  OTU854  OTU883 
##   0.683   0.687   0.691   0.695   0.698   0.702 
## 
## $`Arid dust_Hyperarid dust`
##   OTU6  OTU65 OTU838  OTU55 
##  0.492  0.652  0.697  0.730 
## 
## $`Arid dust_Arid limestone`
##    OTU6   OTU65   OTU20   OTU40  OTU838  OTU225  OTU422  OTU596   OTU73   OTU46   OTU11 
##   0.112   0.222   0.292   0.357   0.385   0.402   0.419   0.435   0.451   0.464   0.477 
##  OTU388  OTU119   OTU29   OTU18   OTU34  OTU746  OTU711   OTU16  OTU235  OTU854  OTU174 
##   0.488   0.499   0.509   0.519   0.529   0.538   0.547   0.556   0.564   0.573   0.581 
##  OTU299  OTU194   OTU68  OTU545   OTU37  OTU925   OTU41  OTU115  OTU140  OTU356   OTU60 
##   0.589   0.596   0.603   0.609   0.616   0.623   0.629   0.635   0.640   0.646   0.651 
##  OTU137  OTU197  OTU166  OTU605   OTU69   OTU55 OTU1089   OTU27  OTU218   OTU48   OTU45 
##   0.656   0.661   0.666   0.671   0.676   0.681   0.685   0.690   0.694   0.698   0.702 
## 
## $`Arid dust_Hyperarid dolomite`
##   OTU1   OTU2   OTU3   OTU7   OTU5  OTU65   OTU9  OTU18   OTU8  OTU17  OTU41  OTU16 
##  0.153  0.236  0.317  0.382  0.415  0.445  0.470  0.495  0.517  0.538  0.559  0.576 
##  OTU11 OTU936  OTU20  OTU28  OTU12  OTU10   OTU6  OTU15  OTU33  OTU14 
##  0.593  0.609  0.624  0.638  0.653  0.666  0.677  0.687  0.696  0.706 
## 
## $`Arid dust_Arid loess soil`
##   OTU65   OTU25   OTU88   OTU62   OTU11  OTU838   OTU68  OTU596  OTU177   OTU78  OTU133 
##  0.0760  0.0986  0.1205  0.1406  0.1597  0.1783  0.1907  0.2015  0.2119  0.2224  0.2320 
##  OTU144   OTU46  OTU115   OTU67   OTU16  OTU156  OTU388  OTU116  OTU137  OTU197  OTU100 
##  0.2412  0.2501  0.2587  0.2669  0.2742  0.2815  0.2885  0.2950  0.3013  0.3076  0.3139 
##   OTU91  OTU687  OTU746  OTU711   OTU73  OTU412  OTU194  OTU422  OTU160  OTU218  OTU152 
##  0.3198  0.3256  0.3312  0.3367  0.3423  0.3473  0.3521  0.3569  0.3615  0.3661  0.3705 
##   OTU53  OTU131  OTU135  OTU356  OTU125  OTU163   OTU37  OTU556  OTU311  OTU130  OTU214 
##  0.3749  0.3789  0.3827  0.3866  0.3904  0.3940  0.3975  0.4011  0.4046  0.4081  0.4116 
##  OTU227  OTU240  OTU341  OTU233  OTU854  OTU648  OTU101   OTU92   OTU55  OTU716  OTU220 
##  0.4150  0.4184  0.4217  0.4250  0.4283  0.4315  0.4348  0.4380  0.4412  0.4443  0.4474 
##  OTU139  OTU140  OTU278   OTU20  OTU103   OTU60  OTU253  OTU171 OTU1235  OTU107  OTU365 
##  0.4505  0.4536  0.4565  0.4594  0.4623  0.4651  0.4679  0.4706  0.4733  0.4760  0.4787 
##  OTU294  OTU301  OTU647  OTU206  OTU136  OTU231  OTU479 OTU1050 OTU1288   OTU82  OTU248 
##  0.4813  0.4839  0.4864  0.4890  0.4916  0.4941  0.4966  0.4991  0.5015  0.5039  0.5064 
##  OTU360  OTU181  OTU434  OTU945  OTU638 OTU1102  OTU315 OTU1184  OTU457   OTU44  OTU491 
##  0.5087  0.5111  0.5134  0.5157  0.5180  0.5203  0.5226  0.5249  0.5271  0.5294  0.5316 
##  OTU472  OTU938  OTU184  OTU471  OTU182  OTU538  OTU352  OTU169  OTU586  OTU191  OTU190 
##  0.5338  0.5360  0.5382  0.5404  0.5425  0.5446  0.5467  0.5488  0.5509  0.5530  0.5551 
##  OTU751  OTU304  OTU251  OTU164  OTU667   OTU69  OTU619  OTU170  OTU154  OTU992 OTU1013 
##  0.5571  0.5592  0.5612  0.5632  0.5652  0.5672  0.5692  0.5712  0.5731  0.5751  0.5771 
##  OTU707  OTU302  OTU725  OTU430 OTU1116  OTU132  OTU466  OTU364  OTU489  OTU166   OTU33 
##  0.5790  0.5809  0.5828  0.5847  0.5866  0.5885  0.5904  0.5922  0.5941  0.5959  0.5978 
## OTU1218  OTU421 OTU1319  OTU545  OTU309  OTU456  OTU562  OTU635  OTU468  OTU610  OTU347 
##  0.5996  0.6015  0.6033  0.6051  0.6068  0.6086  0.6103  0.6121  0.6138  0.6155  0.6171 
##  OTU833  OTU582   OTU41  OTU333    OTU6   OTU27   OTU86  OTU451  OTU162  OTU561  OTU439 
##  0.6188  0.6205  0.6222  0.6238  0.6255  0.6271  0.6287  0.6302  0.6318  0.6334  0.6349 
##  OTU579  OTU255  OTU653  OTU279  OTU368  OTU783   OTU93  OTU298  OTU323 OTU1024 OTU1005 
##  0.6364  0.6380  0.6395  0.6410  0.6425  0.6440  0.6455  0.6470  0.6484  0.6499  0.6513 
##  OTU389  OTU799  OTU348  OTU543  OTU524  OTU258  OTU953  OTU929  OTU174 OTU1100  OTU999 
##  0.6528  0.6542  0.6556  0.6570  0.6584  0.6598  0.6612  0.6625  0.6639  0.6652  0.6665 
##  OTU705  OTU199 OTU1049 OTU1242  OTU449  OTU303  OTU232  OTU765  OTU499   OTU10 OTU1011 
##  0.6678  0.6691  0.6704  0.6717  0.6730  0.6742  0.6754  0.6767  0.6779  0.6791  0.6803 
##  OTU595  OTU697  OTU548  OTU353  OTU310   OTU28 OTU1170  OTU404  OTU141  OTU277  OTU469 
##  0.6815  0.6827  0.6839  0.6851  0.6863  0.6875  0.6887  0.6898  0.6910  0.6922  0.6933 
##  OTU883  OTU557   OTU95   OTU29 OTU1108  OTU641 
##  0.6944  0.6956  0.6967  0.6978  0.6990  0.7001 
## 
## $`Hyperarid loess soil_Hyperarid dust`
##    OTU6   OTU55   OTU90   OTU11   OTU94  OTU187   OTU93  OTU167  OTU121   OTU99  OTU144 
##   0.455   0.493   0.518   0.536   0.551   0.565   0.578   0.589   0.600   0.610   0.619 
##    OTU9  OTU105  OTU340  OTU298  OTU115  OTU640  OTU715   OTU88  OTU197  OTU221  OTU322 
##   0.627   0.634   0.641   0.648   0.654   0.661   0.667   0.674   0.680   0.685   0.690 
## OTU1047   OTU16  OTU484 
##   0.695   0.700   0.704 
## 
## $`Hyperarid loess soil_Arid limestone`
##    OTU6   OTU20   OTU40   OTU90  OTU225   OTU11   OTU73  OTU422  OTU119   OTU29  OTU187 
##   0.207   0.274   0.338   0.356   0.373   0.389   0.403   0.418   0.429   0.439   0.449 
##   OTU46  OTU388   OTU18  OTU167   OTU34   OTU93  OTU299  OTU235  OTU121  OTU174   OTU99 
##   0.459   0.469   0.478   0.487   0.495   0.504   0.512   0.520   0.527   0.535   0.541 
##  OTU925  OTU854  OTU545  OTU144   OTU37  OTU197  OTU140   OTU68   OTU16  OTU340  OTU298 
##   0.548   0.554   0.560   0.566   0.572   0.578   0.584   0.589   0.594   0.599   0.604 
##  OTU605  OTU640   OTU69  OTU715  OTU105   OTU41  OTU137   OTU88   OTU27 OTU1089   OTU60 
##   0.609   0.614   0.618   0.623   0.628   0.632   0.637   0.641   0.645   0.649   0.653 
##   OTU45  OTU221  OTU166  OTU218  OTU261  OTU163   OTU81  OTU115  OTU322  OTU259 OTU1047 
##   0.658   0.662   0.665   0.669   0.673   0.677   0.680   0.684   0.687   0.690   0.693 
##  OTU172  OTU939   OTU67 
##   0.696   0.699   0.702 
## 
## $`Hyperarid loess soil_Hyperarid dolomite`
##   OTU1   OTU2   OTU3   OTU7   OTU6   OTU5   OTU9  OTU18   OTU8  OTU17  OTU41  OTU16 
##  0.150  0.232  0.312  0.374  0.421  0.454  0.478  0.501  0.523  0.544  0.564  0.580 
## OTU936  OTU11  OTU28  OTU12  OTU20  OTU10  OTU15  OTU14  OTU13  OTU45 
##  0.595  0.610  0.625  0.639  0.653  0.666  0.676  0.686  0.694  0.703 
## 
## $`Hyperarid loess soil_Arid loess soil`
##    OTU6   OTU25   OTU62   OTU88   OTU90   OTU11   OTU68  OTU177   OTU78  OTU133  OTU156 
##   0.117   0.141   0.161   0.180   0.192   0.204   0.216   0.226   0.237   0.247   0.254 
##  OTU187   OTU46  OTU116   OTU67  OTU137  OTU100  OTU687  OTU388  OTU115  OTU121   OTU73 
##   0.262   0.269   0.275   0.281   0.287   0.293   0.299   0.305   0.311   0.316   0.321 
##  OTU412   OTU91  OTU167   OTU93   OTU16   OTU99  OTU160  OTU218  OTU144  OTU131  OTU135 
##   0.327   0.332   0.337   0.342   0.347   0.352   0.357   0.361   0.366   0.370   0.374 
##   OTU53  OTU556  OTU152  OTU130  OTU125  OTU227  OTU340  OTU214  OTU233  OTU640  OTU341 
##   0.378   0.381   0.385   0.389   0.392   0.396   0.399   0.403   0.406   0.410   0.413 
##  OTU311  OTU648  OTU422  OTU716  OTU105  OTU197  OTU163  OTU140   OTU44   OTU37   OTU92 
##   0.416   0.420   0.423   0.426   0.430   0.433   0.436   0.439   0.442   0.445   0.448 
##  OTU240  OTU715  OTU139  OTU253  OTU221  OTU298  OTU101  OTU171 OTU1235  OTU107  OTU365 
##   0.451   0.454   0.457   0.460   0.463   0.466   0.469   0.472   0.474   0.477   0.480 
##  OTU491  OTU103  OTU647  OTU479 OTU1047 OTU1288  OTU278  OTU322  OTU136 OTU1102 OTU1050 
##   0.482   0.485   0.488   0.490   0.493   0.495   0.498   0.500   0.503   0.506   0.508 
##  OTU206  OTU360  OTU220  OTU248  OTU231   OTU48  OTU638  OTU945  OTU315  OTU294  OTU181 
##   0.510   0.513   0.515   0.518   0.520   0.522   0.525   0.527   0.529   0.531   0.534 
##  OTU190  OTU471  OTU172  OTU169  OTU457   OTU82  OTU191 OTU1013  OTU472  OTU182  OTU251 
##   0.536   0.538   0.540   0.542   0.545   0.547   0.549   0.551   0.553   0.555   0.557 
##  OTU619  OTU184  OTU352  OTU938  OTU154  OTU707  OTU304  OTU538  OTU386 OTU1116  OTU582 
##   0.559   0.561   0.564   0.566   0.568   0.570   0.572   0.574   0.576   0.578   0.580 
##  OTU751  OTU434   OTU20 OTU1319 OTU1218  OTU992  OTU309  OTU456  OTU364  OTU302   OTU69 
##   0.582   0.583   0.585   0.587   0.589   0.591   0.593   0.595   0.597   0.598   0.600 
##  OTU468  OTU725   OTU86  OTU466  OTU562 OTU1184  OTU347  OTU430  OTU164   OTU60  OTU451 
##   0.602   0.604   0.605   0.607   0.609   0.611   0.612   0.614   0.616   0.617   0.619 
##  OTU635  OTU489  OTU854  OTU610  OTU132  OTU439  OTU255 OTU1046  OTU421  OTU170  OTU543 
##   0.621   0.622   0.624   0.625   0.627   0.629   0.630   0.632   0.633   0.635   0.636 
##  OTU579 OTU1024   OTU27  OTU323  OTU929  OTU368  OTU953  OTU799  OTU545  OTU258 OTU1282 
##   0.638   0.639   0.641   0.642   0.644   0.645   0.647   0.648   0.650   0.651   0.652 
##  OTU267   OTU28 OTU1100  OTU277  OTU279  OTU667  OTU199  OTU705  OTU999  OTU232   OTU95 
##   0.654   0.655   0.657   0.658   0.659   0.661   0.662   0.663   0.665   0.666   0.667 
##  OTU303  OTU836 OTU1242  OTU653    OTU3  OTU141  OTU697  OTU273  OTU499   OTU29 OTU1011 
##   0.669   0.670   0.671   0.672   0.674   0.675   0.676   0.677   0.679   0.680   0.681 
##  OTU389  OTU162 OTU1108  OTU166  OTU595  OTU524  OTU185  OTU765   OTU41  OTU404  OTU641 
##   0.682   0.683   0.685   0.686   0.687   0.688   0.689   0.691   0.692   0.693   0.694 
##  OTU557 OTU1005 OTU1049   OTU10 OTU1101  OTU449 
##   0.695   0.696   0.698   0.699   0.700   0.701 
## 
## $`Hyperarid dust_Arid limestone`
##   OTU6  OTU20  OTU40  OTU55 OTU225 OTU422  OTU73  OTU11  OTU46  OTU94 OTU388  OTU29 
##  0.383  0.442  0.497  0.524  0.539  0.553  0.566  0.578  0.589  0.600  0.609  0.618 
## OTU119  OTU18  OTU34 OTU235  OTU16 OTU854 OTU174 OTU299  OTU68 OTU545   OTU9  OTU37 
##  0.627  0.636  0.644  0.651  0.659  0.666  0.673  0.680  0.685  0.691  0.697  0.702 
## 
## $`Hyperarid dust_Hyperarid dolomite`
##   OTU6   OTU1   OTU2   OTU3   OTU7   OTU5  OTU18   OTU9   OTU8  OTU17  OTU41  OTU11 
##  0.144  0.281  0.357  0.430  0.487  0.517  0.538  0.559  0.579  0.598  0.617  0.633 
##  OTU16 OTU936  OTU28  OTU20  OTU12 
##  0.648  0.662  0.676  0.689  0.701 
## 
## $`Hyperarid dust_Arid loess soil`
##    OTU6   OTU55   OTU25   OTU88   OTU11   OTU62   OTU68  OTU177   OTU78   OTU94  OTU133 
##   0.272   0.292   0.310   0.327   0.343   0.359   0.369   0.377   0.385   0.393   0.401 
##  OTU144   OTU46  OTU115   OTU67  OTU156   OTU16  OTU388  OTU116  OTU137  OTU197  OTU100 
##   0.408   0.415   0.422   0.428   0.434   0.440   0.445   0.450   0.455   0.460   0.465 
##  OTU687   OTU91   OTU73  OTU412  OTU218    OTU9  OTU422  OTU160   OTU53  OTU152  OTU125 
##   0.470   0.474   0.479   0.482   0.486   0.490   0.494   0.497   0.501   0.504   0.508 
##  OTU135  OTU131  OTU311  OTU556  OTU163  OTU130  OTU484  OTU214  OTU227  OTU240   OTU37 
##   0.511   0.514   0.517   0.520   0.523   0.526   0.528   0.531   0.534   0.536   0.539 
##  OTU341  OTU233  OTU854  OTU101  OTU648  OTU140  OTU716   OTU92  OTU220  OTU139   OTU44 
##   0.542   0.544   0.547   0.549   0.552   0.554   0.557   0.559   0.562   0.564   0.567 
##  OTU491   OTU20  OTU278  OTU103  OTU253   OTU60 OTU1235  OTU206  OTU171  OTU107  OTU365 
##   0.569   0.571   0.574   0.576   0.578   0.580   0.582   0.584   0.587   0.589   0.591 
##  OTU294  OTU647  OTU136  OTU231 OTU1050 OTU1102  OTU479 OTU1288   OTU82  OTU248  OTU434 
##   0.593   0.595   0.597   0.599   0.601   0.603   0.605   0.607   0.609   0.610   0.612 
##  OTU638  OTU360  OTU945  OTU181  OTU457  OTU472  OTU938 OTU1184  OTU184  OTU315   OTU33 
##   0.614   0.616   0.618   0.619   0.621   0.623   0.625   0.626   0.628   0.630   0.632 
##  OTU667  OTU471  OTU190 OTU1013  OTU182  OTU538  OTU352  OTU191   OTU86  OTU169  OTU586 
##   0.633   0.635   0.637   0.638   0.640   0.642   0.643   0.645   0.647   0.648   0.650 
##  OTU304  OTU251  OTU164  OTU619  OTU170  OTU751 OTU1116  OTU707  OTU582  OTU302  OTU154 
##   0.651   0.653   0.655   0.656   0.658   0.659   0.661   0.662   0.664   0.665   0.667 
##   OTU69  OTU466  OTU725  OTU430  OTU132  OTU545  OTU489  OTU166   OTU48  OTU992  OTU421 
##   0.668   0.670   0.671   0.673   0.674   0.676   0.677   0.679   0.680   0.682   0.683 
## OTU1218 OTU1319  OTU456  OTU309  OTU364  OTU635  OTU437  OTU610  OTU562  OTU298  OTU468 
##   0.685   0.686   0.687   0.689   0.690   0.692   0.693   0.694   0.696   0.697   0.698 
##  OTU347  OTU333 
##   0.700   0.701 
## 
## $`Arid limestone_Hyperarid dolomite`
##   OTU1   OTU2   OTU3   OTU6   OTU7   OTU5   OTU9   OTU8  OTU18  OTU17  OTU41  OTU40 
##  0.144  0.224  0.302  0.361  0.419  0.451  0.474  0.496  0.516  0.537  0.554  0.570 
##  OTU11 OTU936  OTU16  OTU28  OTU12  OTU20  OTU10  OTU15  OTU14  OTU13  OTU33 
##  0.585  0.600  0.615  0.629  0.642  0.656  0.669  0.679  0.688  0.696  0.705 
## 
## $`Arid limestone_Arid loess soil`
##    OTU6   OTU40   OTU20   OTU25   OTU88   OTU62   OTU11  OTU225  OTU177   OTU78  OTU133 
##  0.0976  0.1375  0.1768  0.1973  0.2164  0.2334  0.2485  0.2580  0.2674  0.2765  0.2848 
##   OTU73   OTU68  OTU119  OTU144   OTU67  OTU156  OTU422   OTU18   OTU29   OTU34  OTU100 
##  0.2931  0.3001  0.3071  0.3139  0.3207  0.3273  0.3334  0.3394  0.3450  0.3506  0.3560 
##  OTU116   OTU91  OTU687   OTU46  OTU299  OTU388  OTU235  OTU197  OTU115  OTU218  OTU412 
##  0.3613  0.3664  0.3714  0.3762  0.3810  0.3858  0.3906  0.3952  0.3995  0.4039  0.4082 
##  OTU160  OTU174   OTU53  OTU152  OTU925  OTU135  OTU137   OTU37  OTU854  OTU545  OTU163 
##  0.4123  0.4163  0.4202  0.4242  0.4281  0.4317  0.4353  0.4386  0.4420  0.4452  0.4484 
##  OTU125  OTU130  OTU131  OTU556  OTU605  OTU311   OTU69  OTU140  OTU341  OTU214   OTU27 
##  0.4516  0.4547  0.4578  0.4609  0.4639  0.4670  0.4700  0.4729  0.4758  0.4788  0.4817 
##  OTU233  OTU648  OTU240   OTU16   OTU92   OTU44  OTU491  OTU139  OTU220  OTU227  OTU278 
##  0.4846  0.4874  0.4903  0.4931  0.4959  0.4987  0.5014  0.5041  0.5068  0.5094  0.5121 
##  OTU101 OTU1089  OTU103  OTU171   OTU45  OTU253  OTU107  OTU261  OTU365  OTU206  OTU231 
##  0.5147  0.5172  0.5198  0.5222  0.5246  0.5270  0.5294  0.5317  0.5341  0.5363  0.5386 
## OTU1235   OTU41  OTU479 OTU1288 OTU1102   OTU81 OTU1050  OTU294  OTU181   OTU60  OTU945 
##  0.5409  0.5431  0.5453  0.5475  0.5497  0.5519  0.5540  0.5561  0.5581  0.5602  0.5622 
##   OTU82   OTU48  OTU360  OTU472  OTU471  OTU136  OTU169  OTU248  OTU315  OTU184  OTU638 
##  0.5642  0.5661  0.5681  0.5701  0.5721  0.5740  0.5759  0.5779  0.5798  0.5817  0.5836 
##  OTU182  OTU352  OTU716  OTU647  OTU191  OTU349  OTU457  OTU938 OTU1013  OTU751  OTU619 
##  0.5855  0.5874  0.5892  0.5911  0.5930  0.5948  0.5966  0.5984  0.6002  0.6020  0.6038 
##  OTU164  OTU166  OTU251  OTU190  OTU154  OTU434  OTU707 OTU1116 OTU1218  OTU302  OTU489 
##  0.6055  0.6073  0.6090  0.6107  0.6124  0.6141  0.6157  0.6174  0.6190  0.6207  0.6223 
##  OTU421  OTU582  OTU286    OTU7  OTU259  OTU667  OTU364  OTU456 OTU1319  OTU298  OTU992 
##  0.6240  0.6256  0.6272  0.6288  0.6304  0.6320  0.6336  0.6351  0.6367  0.6383  0.6398 
##  OTU562  OTU304  OTU468  OTU610  OTU170  OTU347  OTU939   OTU86  OTU430  OTU246  OTU239 
##  0.6413  0.6428  0.6443  0.6458  0.6473  0.6488  0.6503  0.6517  0.6531  0.6545  0.6558 
##  OTU949  OTU255  OTU439  OTU466  OTU132  OTU530  OTU579  OTU368  OTU362   OTU28  OTU451 
##  0.6572  0.6586  0.6599  0.6613  0.6626  0.6639  0.6652  0.6665  0.6678  0.6691  0.6704 
##  OTU653 OTU1299  OTU309  OTU333  OTU399  OTU323  OTU953  OTU348  OTU162 OTU1024  OTU389 
##  0.6717  0.6730  0.6743  0.6755  0.6768  0.6781  0.6793  0.6806  0.6818  0.6830  0.6842 
## OTU1005  OTU929  OTU524 OTU1100  OTU586   OTU95  OTU279  OTU799   OTU87 OTU1101  OTU232 
##  0.6854  0.6866  0.6878  0.6890  0.6901  0.6913  0.6924  0.6936  0.6947  0.6959  0.6970 
##  OTU725  OTU303  OTU999 
##  0.6981  0.6993  0.7004 
## 
## $`Hyperarid dolomite_Arid loess soil`
##   OTU1   OTU2   OTU3   OTU7   OTU5   OTU9  OTU18   OTU8  OTU17  OTU41 OTU936  OTU28 
##  0.132  0.206  0.279  0.331  0.360  0.382  0.402  0.421  0.440  0.457  0.471  0.484 
##  OTU12  OTU16  OTU10  OTU11  OTU20   OTU6  OTU15  OTU14  OTU13  OTU24  OTU33  OTU45 
##  0.497  0.509  0.521  0.533  0.543  0.553  0.562  0.571  0.579  0.586  0.593  0.601 
##  OTU88  OTU25  OTU54  OTU62  OTU34  OTU39  OTU47  OTU19  OTU22  OTU35  OTU68  OTU32 
##  0.608  0.615  0.622  0.628  0.634  0.640  0.646  0.651  0.656  0.660  0.664  0.668 
##  OTU29 OTU756  OTU23  OTU37  OTU78  OTU26 OTU177  OTU30 OTU133  OTU46 
##  0.671  0.675  0.678  0.682  0.685  0.689  0.692  0.695  0.698  0.702

GMPR_ord <- ordinate(Rock_weathering_filt3_GMPR, "CAP", "horn", formula = Rock_weathering_filt3_GMPR ~ Climate * Source)
explained <- eigenvals(GMPR_ord)/sum( eigenvals(GMPR_ord)) * 100
explained <- as.numeric(format(round(explained, 1), nsmall = 1))
data2plot <- cbind(scores(GMPR_ord, display = "sites"), sample_data(Rock_weathering_filt3_GMPR))
p_ord <- ggplot(data2plot) +
  geom_point(aes(x = CAP1, y = CAP2, colour = Source, shape = Climate), size = 3, alpha = 2/3 ) +
  scale_colour_manual(values = pom4) +
  stat_ellipse(aes(x = CAP1, y = CAP2, group = Climate), color = "black", alpha = 0.5, type = "norm", level = 0.95, linetype = 2) +
  xlab(label = paste0("CAP1", " (", explained[1],"%)")) + 
  ylab(label = paste0("CAP2", " (", explained[2],"%)")) +
  coord_fixed(sqrt(explained[2] / explained[1])) 
  
print(p_ord)

Test differences between samples on the phylum level

Taxa_tests_phylum <- STAMPR(Rock_weathering_filt3_GMPR, "Phylum", sig_pairs)

## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##      Phylum          
## OTU1 "Proteobacteria"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq     H p.value
## Climate         1   1118 11.28   0.001
## Source          3    412  4.16   0.245
## Climate:Source  1      2  0.02   0.876
## Residuals      28   1740              
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 5, p-value = 0.2
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -57.3  77.1
## sample estimates:
## difference in location 
##                  -8.84 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.9
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -45.1  61.7
## sample estimates:
## difference in location 
##                   3.71 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 3, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -44.6 -10.5
## sample estimates:
## difference in location 
##                  -24.3 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.6
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -31.6  23.3
## sample estimates:
## difference in location 
##                   2.73 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -92.7 -22.9
## sample estimates:
## difference in location 
##                  -41.8 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.006
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -43.7 -14.5
## sample estimates:
## difference in location 
##                  -31.9 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.4
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -9.15  9.09
## sample estimates:
## difference in location 
##                  -3.91 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 3, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -43.18  -5.63
## sample estimates:
## difference in location 
##                  -35.8 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##      Phylum               
## OTU2 "Deinococcus-Thermus"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq     H p.value
## Climate         1    213  2.14   0.143
## Source          3   1475 14.87   0.002
## Climate:Source  1     73  0.73   0.392
## Residuals      28   1513              
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##   0.116 28.897
## sample estimates:
## difference in location 
##                   3.76 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -16.47  -6.63
## sample estimates:
## difference in location 
##                  -12.4 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 1
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -8.04 20.82
## sample estimates:
## difference in location 
##                  0.132 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.07
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.56 12.95
## sample estimates:
## difference in location 
##                   6.28 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##   6.55 16.59
## sample estimates:
## difference in location 
##                     12 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 50, p-value = 0.3
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -11.37   7.95
## sample estimates:
## difference in location 
##                  -5.99 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 40, p-value = 0.02
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##   0.173 24.992
## sample estimates:
## difference in location 
##                   2.55 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -16.14  -6.64
## sample estimates:
## difference in location 
##                    -12 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##      Phylum         
## OTU5 "Bacteroidetes"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq    H p.value
## Climate         1     13 0.13   0.718
## Source          3    822 8.29   0.040
## Climate:Source  1     75 0.75   0.385
## Residuals      28   2363             
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 5, p-value = 0.2
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -68.3  14.0
## sample estimates:
## difference in location 
##                  -27.2 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.5
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -10.4  67.9
## sample estimates:
## difference in location 
##                   29.6 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.3
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.35  4.99
## sample estimates:
## difference in location 
##                   2.07 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.2
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.995 10.098
## sample estimates:
## difference in location 
##                   5.63 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.08
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.822 15.087
## sample estimates:
## difference in location 
##                   7.65 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 50, p-value = 0.2
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -6.95  1.65
## sample estimates:
## difference in location 
##                  -3.57 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.3
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -5.57  2.83
## sample estimates:
## difference in location 
##                  -1.64 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.7
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -7.94  5.14
## sample estimates:
## difference in location 
##                  -2.62 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##      Phylum         
## OTU7 "Cyanobacteria"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq    H p.value
## Climate         1     96 0.96   0.326
## Source          3    853 8.61   0.035
## Climate:Source  1     45 0.45   0.500
## Residuals      28   2278             
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.2
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -2.46 18.18
## sample estimates:
## difference in location 
##                   2.96 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 6, p-value = 0.3
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -37.74   2.34
## sample estimates:
## difference in location 
##                  -3.32 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##   0.671 18.087
## sample estimates:
## difference in location 
##                   3.08 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.03
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##   0.0686 24.4378
## sample estimates:
## difference in location 
##                   5.27 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.2
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.591 37.801
## sample estimates:
## difference in location 
##                   4.21 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 70, p-value = 1
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -7.31  5.10
## sample estimates:
## difference in location 
##                  0.263 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.7
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -3.69 14.61
## sample estimates:
## difference in location 
##                   1.13 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.8
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -23.70   4.78
## sample estimates:
## difference in location 
##                  -1.64 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##       Phylum         
## OTU10 "Acidobacteria"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq     H p.value
## Climate         1      2  0.02   0.877
## Source          3   1299 13.10   0.004
## Climate:Source  1     70  0.71   0.399
## Residuals      28   1900              
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.8
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.88  6.84
## sample estimates:
## difference in location 
##                   -0.2 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 5, p-value = 0.2
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -3.89  1.99
## sample estimates:
## difference in location 
##                  -1.61 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 1
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.44  1.14
## sample estimates:
## difference in location 
##               -0.00745 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.2
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.80  2.81
## sample estimates:
## difference in location 
##                   1.67 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.1
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.874  4.205
## sample estimates:
## difference in location 
##                   2.41 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 40, p-value = 0.07
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -2.538  0.111
## sample estimates:
## difference in location 
##                  -1.54 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -10.42  -7.39
## sample estimates:
## difference in location 
##                   -8.6 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 40, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  5.71 9.48
## sample estimates:
## difference in location 
##                   7.04 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##       Phylum          
## OTU20 "Actinobacteria"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq    H p.value
## Climate         1    585 5.90   0.015
## Source          3    761 7.68   0.053
## Climate:Source  1      1 0.01   0.928
## Residuals      28   1926             
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.08
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -10.1  56.9
## sample estimates:
## difference in location 
##                   36.9 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 7, p-value = 0.4
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -44.93   9.86
## sample estimates:
## difference in location 
##                  -6.64 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.1
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -6.17 41.74
## sample estimates:
## difference in location 
##                   20.6 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.6
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -23.1  22.2
## sample estimates:
## difference in location 
##                  -6.06 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.06
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.95 46.69
## sample estimates:
## difference in location 
##                   12.8 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 100, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##   7.17 40.31
## sample estimates:
## difference in location 
##                   21.9 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.2
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -11.0  33.2
## sample estimates:
## difference in location 
##                   17.1 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.3
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -19.1  25.8
## sample estimates:
## difference in location 
##                   15.9 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##       Phylum      
## OTU44 "Firmicutes"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq     H p.value
## Climate         1    362  3.65   0.056
## Source          3   1570 15.83   0.001
## Climate:Source  1      1  0.01   0.917
## Residuals      28   1339              
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -8.62 -4.81
## sample estimates:
## difference in location 
##                  -6.67 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  0.255 8.721
## sample estimates:
## difference in location 
##                   5.34 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 2, p-value = 0.03
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.0126 -0.0336
## sample estimates:
## difference in location 
##                 -0.346 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.5
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.667  2.129
## sample estimates:
## difference in location 
##                  0.128 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 8, p-value = 0.5
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -2.27  4.52
## sample estimates:
## difference in location 
##                 -0.205 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.003
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.661 -0.204
## sample estimates:
## difference in location 
##                 -0.533 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.267 -0.788
## sample estimates:
## difference in location 
##                 -0.998 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.6
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.51  1.12
## sample estimates:
## difference in location 
##                  0.522 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##        Phylum            
## OTU116 "Gemmatimonadetes"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq     H p.value
## Climate         1    536  5.41   0.020
## Source          3   1335 13.46   0.004
## Climate:Source  1     29  0.30   0.586
## Residuals      28   1372              
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.9
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.56  2.37
## sample estimates:
## difference in location 
##                   0.11 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.8
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.594  1.579
## sample estimates:
## difference in location 
##                  0.493 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 5, p-value = 0.07
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -2.630  0.147
## sample estimates:
## difference in location 
##                  -1.28 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -2.865 -0.966
## sample estimates:
## difference in location 
##                  -1.92 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.1
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.115  0.699
## sample estimates:
## difference in location 
##                  0.226 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 100, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  0.068 1.125
## sample estimates:
## difference in location 
##                  0.575 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -5.20 -3.07
## sample estimates:
## difference in location 
##                  -4.26 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 40, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  4.37 5.33
## sample estimates:
## difference in location 
##                   4.96 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##        Phylum       
## OTU225 "Chloroflexi"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq     H p.value
## Climate         1    725  7.31   0.007
## Source          3   1423 14.35   0.002
## Climate:Source  1     17  0.17   0.678
## Residuals      28   1107              
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.08
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.89 27.56
## sample estimates:
## difference in location 
##                   8.69 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.9
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -2.39  2.13
## sample estimates:
## difference in location 
##                  0.262 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 6, p-value = 0.1
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -19.84   5.73
## sample estimates:
## difference in location 
##                   -8.4 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -23.2 -10.8
## sample estimates:
## difference in location 
##                  -21.1 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.8
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.82  2.77
## sample estimates:
## difference in location 
##                  0.134 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 100, p-value = 5e-04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##   4.22 15.57
## sample estimates:
## difference in location 
##                   8.96 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.3
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -15.09   6.63
## sample estimates:
## difference in location 
##                  -6.71 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 40, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  13.7 17.4
## sample estimates:
## difference in location 
##                   16.2

Taxa_tests_order <- STAMPR(Rock_weathering_filt3_GMPR, "Order", sig_pairs)

## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##      Order            
## OTU1 "Burkholderiales"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq     H p.value
## Climate         1    901  9.08   0.003
## Source          3   1292 13.03   0.005
## Climate:Source  1     79  0.80   0.371
## Residuals      28   1000              
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -41.19  -3.36
## sample estimates:
## difference in location 
##                  -22.3 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 1
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -40.2  41.2
## sample estimates:
## difference in location 
##                 -0.356 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 2, p-value = 0.03
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.455 -0.126
## sample estimates:
## difference in location 
##                 -0.297 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  12.7 40.8
## sample estimates:
## difference in location 
##                   34.2 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.08
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.325 43.909
## sample estimates:
## difference in location 
##                   34.8 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 9, p-value = 3e-04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -36.5 -15.3
## sample estimates:
## difference in location 
##                  -34.7 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.134 -0.393
## sample estimates:
## difference in location 
##                 -0.743 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 3, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -40.5 -12.0
## sample estimates:
## difference in location 
##                  -33.8 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##      Order               
## OTU5 "Sphingobacteriales"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq     H p.value
## Climate         1    184  1.85   0.174
## Source          3   1245 12.56   0.006
## Climate:Source  1     11  0.11   0.736
## Residuals      28   1833              
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 8, p-value = 0.5
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.110  0.842
## sample estimates:
## difference in location 
##                 -0.309 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 5, p-value = 0.2
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -13.08   1.13
## sample estimates:
## difference in location 
##                  -6.12 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.7
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.664  0.764
## sample estimates:
## difference in location 
##                 0.0192 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.1
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.51 10.25
## sample estimates:
## difference in location 
##                   6.49 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.1
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.478 13.695
## sample estimates:
## difference in location 
##                   6.46 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.005
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -8.517 -0.853
## sample estimates:
## difference in location 
##                  -6.14 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -4.33 -1.61
## sample estimates:
## difference in location 
##                     -3 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.6
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -8.04  3.57
## sample estimates:
## difference in location 
##                  -3.72 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##      Order              
## OTU6 "Enterobacteriales"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq     H p.value
## Climate         1     71  0.71   0.399
## Source          3   2314 23.34   0.000
## Climate:Source  1     64  0.65   0.422
## Residuals      28    824              
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.2
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.571 91.132
## sample estimates:
## difference in location 
##                   3.55 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.08
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -10.44   1.91
## sample estimates:
## difference in location 
##                   1.69 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 3, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -49.50  -5.47
## sample estimates:
## difference in location 
##                  -21.5 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -51.7 -22.4
## sample estimates:
## difference in location 
##                  -26.6 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -84.2 -55.6
## sample estimates:
## difference in location 
##                  -69.9 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 100, p-value = 4e-04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  1.93 8.06
## sample estimates:
## difference in location 
##                   5.11 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 40, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##   1.3 17.4
## sample estimates:
## difference in location 
##                   5.33 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 8, p-value = 0.2
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.5844  0.0654
## sample estimates:
## difference in location 
##                 -0.103 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##      Order         
## OTU7 "SubsectionII"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq    H p.value
## Climate         1    174 1.76   0.185
## Source          3    717 7.23   0.065
## Climate:Source  1      2 0.02   0.876
## Residuals      28   2379             
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.8
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.05 14.87
## sample estimates:
## difference in location 
##                  0.195 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 4, p-value = 0.2
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -33.557   0.854
## sample estimates:
## difference in location 
##                  -3.54 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.6
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.27  9.15
## sample estimates:
## difference in location 
##                  0.518 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.03
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##   0.158 23.911
## sample estimates:
## difference in location 
##                   4.18 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.1
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.365 33.663
## sample estimates:
## difference in location 
##                   4.55 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 40, p-value = 0.08
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -8.94  1.06
## sample estimates:
## difference in location 
##                  -1.22 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.8
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.578  9.034
## sample estimates:
## difference in location 
##                  0.213 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 5, p-value = 0.07
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -23.792   0.123
## sample estimates:
## difference in location 
##                  -3.89 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##      Order        
## OTU9 "Rhizobiales"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq    H p.value
## Climate         1    880 8.88  0.0029
## Source          3    547 5.51  0.1378
## Climate:Source  1    400 4.04  0.0445
## Residuals      28   1445             
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 9, p-value = 0.6
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -5.88  2.95
## sample estimates:
## difference in location 
##                  -1.47 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 6, p-value = 0.3
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -11.7   5.9
## sample estimates:
## difference in location 
##                  -3.36 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.8
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.99  1.21
## sample estimates:
## difference in location 
##                 -0.501 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##   0.976 10.129
## sample estimates:
## difference in location 
##                   4.44 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 8, p-value = 0.5
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -7.85  4.60
## sample estimates:
## difference in location 
##                   -1.2 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 6e-04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -7.32 -2.45
## sample estimates:
## difference in location 
##                  -4.61 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -4.59 -2.23
## sample estimates:
## difference in location 
##                  -2.96 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.4
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -7.27  1.28
## sample estimates:
## difference in location 
##                  -1.61 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##       Order       
## OTU10 "Subgroup_4"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq     H p.value
## Climate         1     49  0.50   0.480
## Source          3   1315 13.26   0.004
## Climate:Source  1     73  0.73   0.392
## Residuals      28   1836              
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.8
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.36  6.53
## sample estimates:
## difference in location 
##                 -0.113 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 4, p-value = 0.2
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -4.08  1.32
## sample estimates:
## difference in location 
##                  -1.91 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.6
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.940  0.823
## sample estimates:
## difference in location 
##                 -0.265 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.1
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.556  3.246
## sample estimates:
## difference in location 
##                   1.83 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.08
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.612  4.277
## sample estimates:
## difference in location 
##                    2.4 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.02
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -2.847 -0.324
## sample estimates:
## difference in location 
##                  -1.97 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 3, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -6.17 -4.03
## sample estimates:
## difference in location 
##                   -5.3 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 40, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  1.72 5.44
## sample estimates:
## difference in location 
##                   3.04 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##       Order             
## OTU11 "Sphingomonadales"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq    H p.value
## Climate         1      5 0.05   0.823
## Source          3    596 6.01   0.111
## Climate:Source  1     66 0.67   0.414
## Residuals      28   2605             
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.9
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -5.9 12.8
## sample estimates:
## difference in location 
##                   0.14 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 9, p-value = 0.6
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -8.33  4.10
## sample estimates:
## difference in location 
##                  -0.71 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.8
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -4.13  5.96
## sample estimates:
## difference in location 
##                  0.326 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.6
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -3.23  5.51
## sample estimates:
## difference in location 
##                   1.48 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  1.38 9.58
## sample estimates:
## difference in location 
##                   5.12 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 50, p-value = 0.3
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -3.50  1.09
## sample estimates:
## difference in location 
##                   -1.2 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.4
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -4.00  3.07
## sample estimates:
## difference in location 
##                  -1.06 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.7
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -2.89  2.81
## sample estimates:
## difference in location 
##                 -0.536 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##       Order            
## OTU14 "Caulobacterales"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq     H p.value
## Climate         1    431  4.34   0.037
## Source          3   1248 12.58   0.006
## Climate:Source  1     40  0.40   0.525
## Residuals      28   1554              
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 9, p-value = 0.6
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.070  0.948
## sample estimates:
## difference in location 
##                -0.0385 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 5, p-value = 0.2
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -2.937  0.523
## sample estimates:
## difference in location 
##                 -0.849 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.4
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.431  0.773
## sample estimates:
## difference in location 
##                  0.218 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 40, p-value = 0.02
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  0.281 2.461
## sample estimates:
## difference in location 
##                    1.1 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  0.365 3.036
## sample estimates:
## difference in location 
##                   1.29 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.002
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.680 -0.436
## sample estimates:
## difference in location 
##                 -0.921 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 1
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.432  0.364
## sample estimates:
## difference in location 
##                 0.0155 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -2.0437 -0.0965
## sample estimates:
## difference in location 
##                 -0.961 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##       Order            
## OTU20 "Rubrobacterales"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq     H p.value
## Climate         1    362  3.65   0.056
## Source          3   1284 12.94   0.005
## Climate:Source  1      7  0.07   0.785
## Residuals      28   1619              
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##   1.34 35.28
## sample estimates:
## difference in location 
##                   23.1 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -34.3941  -0.0705
## sample estimates:
## difference in location 
##                   -4.2 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##   5.21 27.55
## sample estimates:
## difference in location 
##                   17.1 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.9
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -6.01 27.58
## sample estimates:
## difference in location 
##                  0.306 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.06
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.173 34.359
## sample estimates:
## difference in location 
##                   4.64 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 100, p-value = 0.03
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##   1.01 21.60
## sample estimates:
## difference in location 
##                   13.5 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##   5.38 24.82
## sample estimates:
## difference in location 
##                   16.8 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.8
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -26.41   5.86
## sample estimates:
## difference in location 
##                    1.7 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##       Order         
## OTU22 "Cytophagales"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq     H p.value
## Climate         1   1165 11.75   0.001
## Source          3     45  0.45   0.929
## Climate:Source  1    282  2.84   0.092
## Residuals      28   1781              
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 7, p-value = 0.4
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -67.5  13.8
## sample estimates:
## difference in location 
##                  -27.7 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##   1.0 67.3
## sample estimates:
## difference in location 
##                   34.9 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.3
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.07  5.47
## sample estimates:
## difference in location 
##                   1.34 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.3
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.839  0.353
## sample estimates:
## difference in location 
##                 -0.279 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.06
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.195  1.887
## sample estimates:
## difference in location 
##                  0.542 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 100, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  0.416 3.920
## sample estimates:
## difference in location 
##                   2.37 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.5
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.87  5.15
## sample estimates:
## difference in location 
##                   1.17 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.03
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  0.155 1.863
## sample estimates:
## difference in location 
##                   1.16 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##       Order          
## OTU30 "Micrococcales"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq    H p.value
## Climate         1    265 2.68   0.102
## Source          3    750 7.56   0.056
## Climate:Source  1     34 0.34   0.560
## Residuals      28   2223             
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 2, p-value = 0.08
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -5.21  4.63
## sample estimates:
## difference in location 
##                  -2.18 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.08
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -3.83  5.11
## sample estimates:
## difference in location 
##                   2.14 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.3
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.532  1.477
## sample estimates:
## difference in location 
##                  0.271 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.3
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.512  0.787
## sample estimates:
## difference in location 
##                  0.203 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 7, p-value = 0.4
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.50  5.57
## sample estimates:
## difference in location 
##                 -0.228 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 80, p-value = 0.7
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.220  0.369
## sample estimates:
## difference in location 
##                 0.0729 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 4, p-value = 0.05
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.526  0.268
## sample estimates:
## difference in location 
##                  -1.07 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 30, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  0.422 1.495
## sample estimates:
## difference in location 
##                    1.1 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##       Order       
## OTU33 "Frankiales"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq     H p.value
## Climate         1     65 0.655   0.418
## Source          3    263 2.649   0.449
## Climate:Source  1     10 0.097   0.756
## Residuals      28   2935              
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.5
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -2.72 10.23
## sample estimates:
## difference in location 
##                   1.11 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 8, p-value = 0.5
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -6.78  2.83
## sample estimates:
## difference in location 
##                 -0.485 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.9
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.57  4.26
## sample estimates:
## difference in location 
##                  0.298 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.8
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -2.58  4.27
## sample estimates:
## difference in location 
##                 -0.159 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.3
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.786  6.561
## sample estimates:
## difference in location 
##                   1.09 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 80, p-value = 0.6
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.37  1.65
## sample estimates:
## difference in location 
##                  0.569 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.9
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.02  2.98
## sample estimates:
## difference in location 
##                 -0.136 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.7
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -4.11  1.80
## sample estimates:
## difference in location 
##                  0.471 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##       Order          
## OTU40 "Deinococcales"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq     H p.value
## Climate         1     25  0.25   0.617
## Source          3   1445 14.57   0.002
## Climate:Source  1    191  1.92   0.165
## Residuals      28   1612              
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##   0.116 28.897
## sample estimates:
## difference in location 
##                   3.76 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -7.347 -0.588
## sample estimates:
## difference in location 
##                   -2.5 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 1
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -8.04 20.82
## sample estimates:
## difference in location 
##                  0.132 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.3
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -7.13  2.03
## sample estimates:
## difference in location 
##                  -2.58 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  0.514 7.469
## sample estimates:
## difference in location 
##                   2.25 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 80, p-value = 0.6
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -1.34 18.29
## sample estimates:
## difference in location 
##                  0.952 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 40, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##   0.324 25.016
## sample estimates:
## difference in location 
##                   2.69 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -4.205 -0.685
## sample estimates:
## difference in location 
##                  -2.53 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##       Order                
## OTU73 "Solirubrobacterales"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq     H p.value
## Climate         1    671  6.76   0.009
## Source          3   1220 12.31   0.006
## Climate:Source  1      4  0.04   0.846
## Residuals      28   1378              
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.08
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.235 27.641
## sample estimates:
## difference in location 
##                   4.61 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 5, p-value = 0.2
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -2.935  0.261
## sample estimates:
## difference in location 
##                 -0.496 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 1
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -4.21  9.96
## sample estimates:
## difference in location 
##                 -0.109 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -5.29 -2.54
## sample estimates:
## difference in location 
##                  -4.22 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.1
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.176  3.066
## sample estimates:
## difference in location 
##                  0.575 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 100, p-value = 0.002
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##   1.2 11.8
## sample estimates:
## difference in location 
##                   3.69 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.9
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -4.31 10.07
## sample estimates:
## difference in location 
##                  -0.42 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 40, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  2.04 5.95
## sample estimates:
## difference in location 
##                   3.96 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##        Order             
## OTU144 "Acidimicrobiales"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq     H p.value
## Climate         1    403  4.06   0.044
## Source          3   1958 19.75   0.000
## Climate:Source  1     37  0.37   0.542
## Residuals      28    875              
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.08
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.277  1.875
## sample estimates:
## difference in location 
##                  0.947 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 8, p-value = 0.5
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.695  0.294
## sample estimates:
## difference in location 
##                -0.0769 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -8.06 -2.73
## sample estimates:
## difference in location 
##                  -4.38 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -8.81 -3.72
## sample estimates:
## difference in location 
##                  -5.31 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.06
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.00973  0.70729
## sample estimates:
## difference in location 
##                  0.204 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 100, p-value = 0.002
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  0.352 1.165
## sample estimates:
## difference in location 
##                  0.871 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -3.35 -1.70
## sample estimates:
## difference in location 
##                  -2.35 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 40, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  2.65 4.11
## sample estimates:
## difference in location 
##                   3.12 
## 
## Taxonomy Table:     [1 taxa by 1 taxonomic ranks]:
##        Order         
## OTU225 "JG30-KF-CM45"
## 
## DV:  Abundance 
## Observations:  34 
## D:  1 
## MS total:  99.2 
## 
##                Df Sum Sq     H p.value
## Climate         1   1051 10.59   0.001
## Source          3   1026 10.34   0.016
## Climate:Source  1     20  0.21   0.650
## Residuals      28   1176              
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.08
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.335 20.313
## sample estimates:
## difference in location 
##                   4.14 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 10, p-value = 0.8
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.407  0.404
## sample estimates:
## difference in location 
##                0.00744 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.9
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -3.84 11.81
## sample estimates:
## difference in location 
##                  0.601 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 0, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -4.80 -2.22
## sample estimates:
## difference in location 
##                  -4.48 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.3
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -0.155  0.514
## sample estimates:
## difference in location 
##                  0.116 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 100, p-value = 3e-04
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  2.58 6.32
## sample estimates:
## difference in location 
##                   4.24 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 20, p-value = 0.9
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -3.81 10.33
## sample estimates:
## difference in location 
##                 -0.209 
## 
## 
##  Wilcoxon rank sum test with continuity correction
## 
## data:  Abundance by Climate.Source
## W = 40, p-value = 0.01
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  3.70 4.57
## sample estimates:
## difference in location 
##                    4.3

Ternary plots

For the arid samples

Rock_weathering_filt3_GMPR_Arid_rel <- transform_sample_counts(Rock_weathering_filt3_GMPR_Arid, function(x) x / sum(x) ) # rel abundance
Rock_weathering_filt3_GMPR_Arid_merged <- merge_samples(Rock_weathering_filt3_GMPR_Arid_rel, "Source", fun = mean) # merge by source
Rock_weathering_filt3_GMPR_Arid_merged_rel <- transform_sample_counts(Rock_weathering_filt3_GMPR_Arid_merged, function(x) x / sum(x) ) # rel abundance per source
meandf <- as(otu_table(Rock_weathering_filt3_GMPR_Arid_merged_rel), "matrix")
if (!taxa_are_rows(Rock_weathering_filt3_GMPR_Arid_merged_rel)) { meandf <- t(meandf) }
abundance <- rowSums(meandf) / sum(meandf) * 100

Arid4Ternary <- data.frame(
  meandf,
  Abundance = abundance,
  Phylum = tax_table(Rock_weathering_filt3_GMPR_Arid_merged_rel)[, "Phylum"]
)
# Arid4Ternary <- dplyr::rename(Arid4Ternary, Loess_soil = Loess.soil)

Arid4Ternary$Phylum <-
  factor(Arid4Ternary$Phylum, levels = c(levels(Arid4Ternary$Phylum), 'Rare'))
Arid4Ternary$Phylum[Arid4Ternary$Phylum %in% Rare_phyla]  <- "Rare"
Arid4Ternary$Phylum %<>% 
  factor(., levels = Taxa_rank$Phylum) %>% 
  fct_relevel(., "Rare", after = Inf)

p_ternary_arid <-
  ggtern(data = Arid4Ternary,
         aes(
           x = Loess.soil,
           y = Dust,
           z = Limestone,
           size = Abundance,
           colour = Phylum
         )) +
  geom_point(alpha = 1 / 2) +
  scale_size(
    range = c(1, 5),
    name = "Abundance (%)"
  ) +
  theme_arrownormal() +
    scale_color_manual(values = pal("d3js")) +
  guides(colour = guide_legend(override.aes = list(size = 3))) +
  labs(x = "Loess soil") + 
  theme(axis.title = element_blank())
print(p_ternary_arid)

For the hyperarid samples

Rock_weathering_filt3_GMPR_Hyperarid_rel <- transform_sample_counts(Rock_weathering_filt3_GMPR_Hyperarid, function(x) x / sum(x) ) # rel abundance
Rock_weathering_filt3_GMPR_Hyperarid_merged <- merge_samples(Rock_weathering_filt3_GMPR_Hyperarid_rel, "Source", fun = mean) # merge by source
Rock_weathering_filt3_GMPR_Hyperarid_merged_rel <- transform_sample_counts(Rock_weathering_filt3_GMPR_Hyperarid_merged, function(x) x / sum(x) ) # rel abundance per source
meandf <- as(otu_table(Rock_weathering_filt3_GMPR_Hyperarid_merged_rel), "matrix")
if (!taxa_are_rows(Rock_weathering_filt3_GMPR_Hyperarid_merged_rel)) { meandf <- t(meandf) }
abundance <- rowSums(meandf) / sum(meandf) * 100

Hyperarid4Ternary <- data.frame(
  meandf,
  Abundance = abundance,
  Phylum = tax_table(Rock_weathering_filt3_GMPR_Hyperarid_merged_rel)[, "Phylum"]
)

Hyperarid4Ternary$Phylum <-
  factor(Hyperarid4Ternary$Phylum, levels = c(levels(Hyperarid4Ternary$Phylum), 'Rare'))
Hyperarid4Ternary$Phylum[Hyperarid4Ternary$Phylum %in% Rare_phyla]  <- "Rare"
Hyperarid4Ternary$Phylum %<>% 
  factor(., levels = Taxa_rank$Phylum) %>% 
  fct_relevel(., "Rare", after = Inf)

p_ternary_hyperarid <-
  ggtern(data = Hyperarid4Ternary,
         aes(
           x = Loess.soil,
           y = Dust,
           z = Dolomite,
           size = Abundance,
           colour = Phylum
         )) +
  geom_point(alpha = 1 / 2) +
  scale_size(
    range = c(1, 5),
    name = "Abundance (%)"
  ) +
  theme_arrownormal() +
  scale_color_manual(values = pal("d3js")) +
  guides(colour = guide_legend(override.aes = list(size = 3))) +
  labs(x = "Loess soil") + 
  theme(axis.title = element_blank())
print(p_ternary_hyperarid)

Combine plots

Combine all sequence analysis plots to make Fig. 3

ternary_legend <-
  get_legend(p_ternary_arid)# + theme(legend.direction = "horizontal"))
ord_legend <- get_legend(p_ord)
top_row <-
  plot_grid(
    p_alpha + theme(
      legend.position = "none",
      panel.spacing = unit(0.5, "lines")
    ),
    p_ord + theme(axis.title.y = element_text(vjust = -3)) ,
    labels = c('A', 'B'),
    label_size = 12,
    align = 'v',
    axis = "tl",
    nrow = 1,
    ncol = 2
  )
bottom_l <-
  plot_grid(
    p_taxa_box + theme(legend.position = "none"),
    labels = c('C'),
    label_size = 12,
    ncol = 1
  )
bottom_r <-
  plot_grid(
    p_ternary_arid + 
      theme(legend.position = "none", 
            plot.margin = unit(c(-0.1, -0.1, -0.1, -0.1), "cm"),
            axis.title = element_blank()),
    p_ternary_hyperarid + 
      theme(legend.position = "none", 
            plot.margin = unit(c(-0.1, -0.1, -0.1, -0.1), "cm"),
            axis.title = element_blank()),
    labels = c('D'),
    label_size = 12,
    align = 'hv',
    axis = "t",
    # rel_widths = c(1, 1, 0.1),
    scale = c(1.2, 1.2),
    nrow = 2,
    ncol = 1
  )

bottom_rows <- plot_grid(bottom_l, 
                         bottom_r,
                         ternary_legend,
                         align = 'h',
                         axis = "l",
                         scale = c(1, 1, 0.08),
                         rel_widths = c(0.5, 0.35, 0.15),
                         nrow = 1, 
                         ncol = 3)
p_all <- plot_grid(top_row, bottom_rows, align = 'v', axis = 'l', nrow = 2, rel_heights = c(0.43, 0.6)) # aligning vertically along the left axis
print(p_all)